Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Georg Krempl"'
This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783031264115
In transductive active learning, the goal is to determine the correct labels for an unlabeled, known dataset. Therefore, we can either ask an oracle to provide the right label at some cost or use the prediction of a classifier which we train on the l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3bde8abb4f4599c55cf44fd1b89404f5
https://doi.org/10.1007/978-3-031-26412-2_29
https://doi.org/10.1007/978-3-031-26412-2_29
Publikováno v:
Advances in Intelligent Data Analysis XIX ISBN: 9783030742508
IDA
IDA
Some data analysis applications comprise datasets, where explanatory variables are expensive or tedious to acquire, but auxiliary data are readily available and might help to construct an insightful training set. An example is neuroimaging research o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d2c4cc80fee9c2d65496ea7c131705b7
https://doi.org/10.1007/978-3-030-74251-5_15
https://doi.org/10.1007/978-3-030-74251-5_15
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030445836
This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5cc138bf51f77e30d3f1479d09412351
Autor:
Georg Krempl, Indre Žliobaite, Dariusz Brzeziński, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi, Myra Spiliopoulou, Jerzy Stefanowski
Publikováno v:
ACM SIGKDD Explorations Newsletter. 16:1-10
Every day, huge volumes of sensory, transactional, and web data are continuously generated as streams, which need to be analyzed online as they arrive. Streaming data can be considered as one of the main sources of what is called big data. While pred
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e3a5da349e56c3b38cd306f4651c9ab8
https://doi.org/10.1145/2674026.2674028
https://doi.org/10.1145/2674026.2674028
Autor:
Georg Krempl, Vera Hofer
Publikováno v:
Computational Statistics & Data Analysis. 57:377-391
A novel statistical methodology for analysing population drift in classification is introduced. Drift denotes changes in the joint distribution of explanatory variables and class labels over time. It entails the deterioration of a classifier's perfor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0930a21afe41cf672e3be5d1b2351e9
https://doi.org/10.1016/j.csda.2012.07.007
https://doi.org/10.1016/j.csda.2012.07.007
A hierarchical tree layout algorithm with an application to corporate management in a change process
Autor:
Vera Hofer, Georg Krempl
Publikováno v:
Expert Systems with Applications. 39:12123-12130
This work presents a hierarchical tree layout algorithm based on iterative rearrangement of subtrees. Using a greedy heuristic, all subtrees of a common parent are rearranged into a forest such that gaps between them are minimized. This heuristic is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d0b22f08e68d26115e5dbe5c3c40784
https://doi.org/10.1016/j.eswa.2012.04.002
https://doi.org/10.1016/j.eswa.2012.04.002
Publikováno v:
I-KNOW
Facing ever increasing volumes of data but limited human annotation capabilities, active learning strategies for selecting the most informative labels gain in importance. However, the choice of an appropriate active learning strategy itself is a comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::981fd22c109e9507c532063493672dc3
https://doi.org/10.1145/2809563.2809594
https://doi.org/10.1145/2809563.2809594
Publikováno v:
Discovery Science ISBN: 9783319242811
Discovery Science
Discovery Science
Facing ever increasing volumes of data but limited human annotation capacities, active learning approaches that allocate these capacities to the labelling of the most valuable instances gain in importance. A particular challenge is the active learnin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e23e5d3de4fde730187710fa2bed1f1e
https://doi.org/10.1007/978-3-319-24282-8_10
https://doi.org/10.1007/978-3-319-24282-8_10
Publikováno v:
Advances in Intelligent Data Analysis XIV ISBN: 9783319244648
IDA
IDA
In recent years, stream-based active learning has become an intensively investigated research topic. In this work, we propose a new algorithm for stream-based active learning that decides immediately whether to acquire a label (selective sampling). T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed8e09c9c82b186516686e9d5079fa30
https://doi.org/10.1007/978-3-319-24465-5_13
https://doi.org/10.1007/978-3-319-24465-5_13